Object detection [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]} is essential to many real-world applications, like autonomous driving, defect detection, and remote sensing. Representative deep-learning-based object detection methods can be roughly categorized into two-stage detectors like Faster RCNN [3]} and one-stage object detectors like YOLO [4]} and RetinaNet [6]}.
While effective, these methods generally rely on many heuristics like anchor generation and rule-based label assignments.
